Helping to Realize “Computer Science for All”: Student Outcomes of Self-Pacing in Introductory Programming Courses


  • Jaime Lester George Mason University



Sparked by a series of national campaigns to increase interest in computer science, computer science departments are inundated with students who are interested in learning how to program. Despite the interest, introductory computer science course have relatively low completion rates (approximately 55% at Mason) and high rates of academic integrity violations. In response to this environment, the Computer Science department at Mason received an external grant to redesign their introductory programming courses to a self-paced, flipped format. Implementation began in Fall 2015 with a quasi-experimental methodology that tracks students from an experimental course and a control group (those who took more traditional introductory CS courses) over the course of the semester. Data collected includes grades on assignments, self-report surveys, and classroom observations.  The purpose of this study is to examine the impact of a self-paced, flipped curricular design in an introductory experiential computer science course on the immediate (in course) completion.  

In this short lightning talk, we will present data from student surveys and classroom observations identifying any difference across the control and experimental groups. Preliminary results identify a significant increase in student completion upwards of a 20% difference across the groups. In addition to increasing knowledge of the impact of self-paced courses on student retention and success in computer science, we offer an alternative method to collect data on classroom observations via the Real-time Observation Classroom Application (ROCA). ROCA allows for efficient data collection and comparison of specific pedagogies to student engagement measures.  

Author Biography

Jaime Lester, George Mason University

**2012 GMU Teacher of Distinction**

**2013 GMU Teaching Excellence Award**